From veterinary studies in China, to machine learning algorithms in Detroit, this two-time Nanodegree program graduate has been on a remarkable career journey.

Xi Palazzolo was going to be a veterinarian. She completed her training in China, then moved to the US to study for a Master’s in Epidemiology. She planned to practice when she graduated. But her hopes were dashed when she discovered few clinics were willing to sponsor her work visa. What was she going to do? She had to find something else, in a different field entirely.

Fate intervened when Xi met her future husband. They moved to Detroit for his job, and she found a role at a university, evaluating the impact of the institution’s programs. She enjoyed the work, but she wanted more for her career.

She sat down with her husband and took a hard look at her situation. What transferable skills did she have? What investments of time and money would different career paths require? What fields genuinely excited her? Data was the answer for Xi, so she started working to build her skills. She enrolled in the Data Analyst Nanodegree program, and started learning the programming languages—like R and Python—she’d need to succeed in the field.

We’re happy to share that Xi recently landed a new role in data, and what’s more, she’s graduated from a second Nanodegree program in Machine Learning! We spoke with her to hear about how she landed an amazing new job in an industry she loves.

It was while you were working at a university that you started thinking about a career change. Can you tell us why that was, and how you went about identifying your next career path?

I’d started to feel the work at the university wasn’t challenging or satisfying enough to hold my interest for the long-term. So, with the support of my friends and family, I wrote down the pros and cons of every possible career move I could think of. I thought about the opportunity cost of every option—how much time they would take, what kind of investment it would take. And I tried to be honest about how interested I was in each option.

After that process, you finally focused on data. What was it about data as a future career that really excited you?

I chose data because of my passion for mathematics and programming, and my curiosity about the insights that drive decision making. At the time, I wanted a career that would continuously challenge me and satisfy my thirst for learning new things. I’d started reading about data science, and I came to realize it was a field that could offer that.

In planning to move to a data role, were there areas you identified where you needed to build new skills?

Yes, I wasn’t that experienced as far as programming goes. I did a little SAS and SQL when I was in graduate school, though it wasn’t in that much depth. I’d listened to a podcast about data science, and they were talking about R, and explaining how powerful it was in things like visualization and statistical analysis. Listening to that really drew me into learning about R, and then other programming languages. I could see those skills would allow me to do more in my career.

People often learn about Udacity through their networks, but you got a recommendation from a little closer to home than that, didn’t you?

My husband is an autonomous systems engineer here in Michigan, and at the same time as I was considering my career options, he started Udacity’s Self Driving Car Engineer Nanodegree program with a group of people from his work. It was through hearing him and his colleagues talk about their program and the projects they were working on that I first learned about Udacity.

And so you enrolled in the Data Analyst Nanodegree program?

Yes. That was where I really found out more about R and first learned about using Python. I found both of them so cool—they both have such different advantages as far as supporting analytics goes.

Even though you hadn’t moved to a new data role yet, did learning new data skills have an impact on your current job?

Yes, when I started the program, my current role was not purely data-related. It was a part of the job, but not my primary responsibility. As I learned more data skills, I made the effort to identify opportunities within my organization where I could implement them. I proactively reached out to colleagues to express my interest in helping with their research projects. Some of those projects became part of my portfolio!

Speaking of your portfolio—as a relative newcomer to programming, how did you find the experience of working on your program’s projects?

At the start of the program, I definitely needed to ask for help with the first couple of projects—reaching out to mentors and other students for help. That was great, and helped my confidence grow, so I was able to complete the rest of the projects independently.

You got a job while still studying in the program, didn’t you?

I did. I started a new role after enrolling in the program—working as an analyst for a healthcare insurance company, helping clients to reduce patient risk.

But while you quite liked that role, you still felt you weren’t quite where you wanted to be in your career. Is that why you enrolled in the Machine Learning Nanodegree program so soon after graduating that Data Analyst program?

Yes, the Machine Learning Nanodegree program was more challenging, but once I’d begun the program, I realized that the applications of machine learning and artificial intelligence were more intriguing for me. I just found it so interesting. So I started looking for a position that was more in line with that area.

What was your next step after graduation?

After I graduated, I updated my skills on LinkedIn. I quickly got a lot of phone calls from recruiters. I was invited to a lot of interviews—including Google! It was pretty remarkable. While I was still working in my previous role, I remember saying to my husband that I’d never had the experience of recruiters chasing after me about different roles. I didn’t know what that would feel like. Now I do, and it was a great feeling!

Was it challenging to connect your past experience with the roles you were being interviewed for?

I already had pretty strong analytical skills that I’d built through many different research projects. I think the key thing I needed to do was emphasize my ability to quickly adapt to working with new data content, and I could prove that through my project portfolio.

So your portfolio of projects was an important part of the interviewing stage of your job hunt?

For a lot of my interviews, I brought along my portfolio, which had a lot of the projects I’d completed in my Nanodegree programs. I think many of the interviewers had never seen someone present that level of portfolio, with so many projects to demonstrate their experience!

“Most of my Udacity projects were built using real-life data, which I think is what really impressed them—I could show my learning connected with real work.”

You’ve now started your new role. Can you tell us about what that involves?

I’m working as an Advanced Analytic consultant for a company in Detroit. I’m going to be working at different client sites to help them develop machine learning algorithms they can apply to their industry to benefit their business. It’s a more commercialized version of machine learning models. I’m really excited about it! I feel like it’s what I have a real passion for.

Finally, I believe your husband has also finished his program. What’s it like to have two Nanodegree program graduates living under one roof?

It means we’ve started talking about algorithms as one of our daily topics of chat at home! Now, if either of us has questions, we can just teach each other. He has already started asking me to explain more about machine learning algorithms!

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Congratulations on your new role Xi! It’s wonderful to see that your diligent career audit identified your new passion and enabled your career step into an exciting field. With your evident passion for machine learning, we can easily imagine that you and your husband will be talking about your shared love of algorithms for many years to come!